System and method for high-content oncology assay

ABSTRACT

The present invention provides an apparatus, system, method and computer program and computer program product for analyzing cellular samples. One embodiment of the apparatus and method provides a multiparameter assay that provides information with respect to cell proliferation, cell cycling and cell death. The multiparameter assay is particularly useful for assessing and screening candidate compounds for anti-cancer utility.

This application is a continuation of U.S. patent application Ser. No.11/726,396 filed Mar. 20, 2007, which is a continuation-in-part of U.S.patent application Ser. No. 10/652,440, filed Aug. 28, 2003 (now U.S.Pat. No. 7,970,549), which claims the benefit of Provisional PatentApplication No. 60/406,714, filed, Aug. 28, 2002, the disclosures ofwhich applications are incorporated herein in their entirety.

BACKGROUND

Cancer is one of the most common causes of mortality in the U.S. Agentsthat can prevent the proliferation of tumor cells and/or induce theirdeath are highly desirable in the fight against cancer. The process oftumor cell proliferation is extremely complex. Understanding tumorproliferation requires precise identification of multiple cell nucleiand detailed analysis of their phases in the cell cycle. Screening foragents able to halt proliferation and/or induce death of tumor and othercancer cells rely largely on biochemical and molecular biologicalapproaches that are laborious and, in many instances, inadequate.Improved methods for screening cellular samples for proliferation, cellcycle phase, and/or death, as well as screening methods for identifyingcompounds capable of halting proliferation and/or inducing death, areneeded.

SUMMARY OF THE INVENTION

In one aspect, the invention provides a system to analyze a cellularsample. An image capture device gathers luminescence intensity valuescorresponding to the nuclei of cells stained with a luminescentDNA-binding reporter molecule. A computer connected to the image capturedevice includes a peripheral interface circuit to receive theluminescence intensity values. A central processing unit is connected tothe peripheral interface circuit. A memory is connected to the centralprocessing unit. The memory operates under the control of the centralprocessing unit. The memory includes an object identification module toidentify and define nuclei of cells captured by the image capturedevice, and one or more of the following modules: a cell proliferationanalysis module to count the defined nuclei, a cell cycle analysismodule that provides information about cell cycling based upon the totalnuclear brightness and standard deviation of nuclear brightness of thedefined nuclei and/or a cell death analysis module that providesinformation about the viability of the cells based upon minimumluminescence intensity values corresponding to the defined nuclei.

In another aspect, the present invention provides a method ofidentifying objects in a sample based upon digital luminescenceintensity values corresponding to the sample. According to the method,preliminary objects comprising groups of at least 50 pixels havingluminescence intensity values above a first threshold (background) levelare identified. An optional roundness parameter may be applied, thevalue of which will depend upon the overall morphology of the cells(e.g., round, oval, etc.) and will be apparent to those of skill in theart. A first mask of these preliminary objects is created, dilated andsubtracted from the digital luminescence intensity values to yield a setof subtracted luminescence intensity values. From the subtractedluminescence intensity values, subtracted objects comprising groupingsof at least 20 pixels having luminescence intensity values above asecond threshold level, which may be the same or different from thefirst threshold level, and which have a specified roundness, which willdepend upon the overall morphology of the cells are identified and asecond mask of the subtracted objects is created. The undilated firstmask is added to the second mask to yield a summed mask. A watershedsplit routine is applied to the summed mask, outlines of the resultantobjects are obtained and the outlines are then applied to the originaldigital data, thereby defining objects in the original digital data.When the sample is a cellular sample stained with a luminescentDNA-binding reporter molecule, the defined objects correspond to nucleiof cells in the cellular sample.

In still another embodiment, the present invention provides a method ofanalyzing a cellular sample for proliferation. According to the method,nuclei corresponding to cells stained with a luminescent DNA-bindingreporter molecule are identified and defined using thepreviously-described method of identifying objects. The defined nucleiare then counted. Determining the number of nuclei in the sample under avariety of conditions provides information about whether the cellularsample is proliferating. Thus, the method is particularly suited foridentifying candidate compounds that inhibit cell proliferation. In oneembodiment, the number of nuclei in a sample of cells treated with acandidate compound of interest as a function of time providesinformation about the ability of the test compound to inhibitproliferation of the cells. In another embodiment, the concentration ofa candidate compound that inhibits 50% of cell proliferation (IC50 orED50) can be determined by counting the number of nuclei of cellularsamples of equal densities as a function of applied compoundconcentration.

In still another aspect, the present information provides a method ofanalyzing the cell cycle of a cell or the cell cycling of a populationof cells. According to the method, nuclei of cells stained with aluminescent DNA-binding reporter molecule are identified as definedusing the previously-described method of identifying objects. For eachdefined nucleus, a total nuclear brightness (“NB”) versus standarddeviation of total nuclear brightness (“SD”) coordinate (or SD vs. NBcoordinate) is obtained based upon the luminescence intensity valuescorresponding thereto. Information about the phase in the cell cycle ofa particular cell, or about the cell cycling of a population of cells,is obtained based upon the coordinates. In one embodiment, a cellcoordinate is filtered through a plurality of filters, each of whichdefines a set of coordinates corresponding to a particular phase in thecell cycle. Passage through or retention on a particular filter providesinformation about which phase in the cell cycle the cell is in. In analternative embodiment, coordinates of a plurality of cells are filteredthrough the plurality of filters and the percentages of cells retainedor passed through each filter calculated. The percentages provideinformation about the cycling of the cell population.

The method can be used in a variety of ways to identify candidatecompounds that have an effect on cell cycling. As a specific example,the percentages of cells treated with a candidate compound of interestthat are retained by each of the various filtered can be compared withthe percentages retained by sister cultures of synchronous controlcells. Differences in the observed percentages indicates the candidatecompound has an effect on the cycling of the cells.

In still another aspect, the present invention provides a sensitivemethod of analyzing a cell for death, whether due to necrosis orapoptosis. According to the method, the minimum nuclear luminescenceintensity (“MNLI”) value corresponding to the nucleus of a cell that hasbeen stained with a luminescent DNA-binding reporter molecule isdetermined. The MNLI value is then assessed to determine whether itfalls outside a range of MNLI values indicative of viable cells. Therange of MNLI values may be a predefined range of values or may be basedupon the MNLI values corresponding to healthy, viable cells. The methodmay be used to analyze necrosis or apoptosis in a variety of contexts,and is particularly useful for analyzing necrosis or apoptosis in cellsthat have been exposed to, or contacted with, a candidate compound inorder to identify compounds capable of inducing cell death.

In another aspect, the present invention provides a high-content assaythat furnishes information on cell proliferation, cell death and cellcycle regulation. According to the method, luminescence intensity valuescorresponding to nuclei of one or more cells in a cellular sample areobtained. Information about cell proliferation, cell death and cellcycle regulation are then calculated from these values, as previouslydescribed.

The high-content assay may be used to analyze cellular samples in avariety of contexts, and is particularly useful for analyzing cells thathave been exposed to, or contacted with, a candidate compound ofinterest to assess the effect(s) of the candidate compound on the cells.For example, the candidate compound may be assessed to determine whetherit inhibits cell proliferation, arrests the cell cycle and/or inducescell death. Quite significantly, owing to the high information contentprovided by the assay, the high-content assay of the invention can beused not only to identify compounds that have potential anti-canceractivity, but to determine the mechanism by which the compounds exerttheir anti-cancer activity. The high-content assay of the inventiontherefore finds particular utility in screening libraries of candidatecompounds to identify those library members that are anti-proliferative,that arrest cell cycle and/or that induce cell death, whether bynecrosis or apoptosis. The ability of the high-content assay of theinvention to distinguish between the mechanisms provides significanttime and cost savings. Thus, information that is typically unavailableuntil late-phase secondary screens have been performed is now obtainableat the early initial screening phase.

The invention also provides computer program, computer program product,and computer code and/or computer memory to direct a computer tofunction in a specified manner. In one embodiment, executableinstructions perform functions and/or processing algorithms that inconjunction with a computing machine identify or define nuclei of cellsstained with a fluorescent DNA-binding reporter molecule based uponluminescence intensity values of the stained cells. Additionalexecutable instructions perform tasks on collected data to provideinformation about cell proliferation, cell cycle regulation and/or celldeath. In one embodiment, information about cell cycle regulation isprovided by executing certain executable instructions in the processorand memory of the computer that calculate a total nuclear brightnessversus standard deviation of nuclear brightness coordinate for eachdefined nucleus in the region. Additional executable instructionsinstruct the computer to compute a histogram of the coordinates. Thehistogram can be analyzed with additional executable instructions toassign each coordinate to a phase in the cell cycle, and/or thehistogram can be output to a display device, which may be a printer, avideo display or other display device, for visual analysis. Informationabout cell proliferation is provided by executing other executableinstructions in the processor and memory (or CPU) of the computer thatdefine and count the number of nuclei within the region. Informationabout cell death is provided by executable instructions that calculateMNLI values of the defined nuclei based upon the nuclear luminescenceintensity values. Additional executable instructions assess whether theMNLI value falls outside a range of MNLI values indicative of viablecells.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 provides a schematic representation of an apparatus of theinvention;

FIG. 2 provides a schematic representation of one method of identifyingnuclei according to the invention;

FIG. 3 provides images illustrating the method of FIG. 2;

FIG. 4A provides images illustrating the greater accuracy in definingnuclei achieved with the object identification module of FIG. 2 ascompared with conventional object identification routines;

FIG. 4B provides a bar graph comparing the accuracy of three differentnuclei identification routines with nuclei identified by visualinspection;

FIG. 5 provides a schematic demonstrating the use of the cellproliferation assay of the invention to measure IC₅₀s or EC₅₀s of cellproliferation;

FIGS. 6A-6B provide schematic representations of exemplary embodimentsof the cell cycle assay of the invention;

FIG. 7 provides a graph of cell cycle data produced by the cell cycleassay of the invention;

FIG. 8 provides cell cycle data for cells treated with representativetest compounds obtained with the cell cycle assay of the inventiondemonstrating the utility of the assay in screening methods to identifycandidate compounds that affect cycling of cells;

FIGS. 9A-9C provide schematic representations of exemplary embodimentsof the cell death assay of the invention;

FIG. 10 provides a graph showing the ability of the cell death assay ofthe invention to identify and distinguish compounds that induce celldeath (taxol) from compounds that do not (DMSO, etoposide); and

FIG. 11 provides a bar graph illustrating the accuracy of the cell deathassay of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 illustrates a system 20 configured in accordance with anembodiment of the invention. The system 20 includes a sample plate 22for holding a cellular sample to be analyzed in accordance with theinvention. The sample plate may be any type of sample plate commonlyemployed in the art for analyzing cellular samples. In one embodiment,the sample plate is a multiwell plate, such as a 96-well plate. Thecells are typically adhered to the bottoms of the wells of the plate,preferably in a layer a single cell deep, using any of a variety ofwell-known techniques for adhering, attaching or fixing cells to cellsample plates. The cells are stained with a luminescent reportermolecule so that they, or their nuclei, can be visualized, as well bedescribed in more detail, below. As a specific example, the cells areadherent cells that are cultured as a confluent or sub-confluent layeron the bottoms of the wells of the sample plate using standardtechniques. Preferably, the position of the sample plate 22 iscontrolled by a plate position controller 24, which provides positioncontrol along an x-axis, y-axis, and z-axis. A light source 26illuminates the sample plate 22. Depending upon the reporter moleculeused to stain the cells, the light source 26 may cause the cells to emitlight. A microscope 28 may be used to observe the sample. An imagecapture device 30 is focused on the sample plate 22. The image capturedevice is capable of receiving and preferably digitizing luminescenceintensity values from the sample. In one embodiment of the invention,the image capture device 30 is a digital camera.

The image capture device 30 and the plate position controller 24preferably operate under the control of a computer 40. The computer 40includes peripheral interface circuits 42, which are connected to theplate position controller 24 and the image capture device 30. A centralprocessing unit 44 is connected to the peripheral interface circuits 42via a bus 46. Input/output devices 48 are also connected to the systembus 46. By way of example, the input/output devices 48 may include akeyboard, mouse, joystick, video monitor, printer, and the like.

A memory 50 is also connected to the system bus 46. The memory 50 storesa set of executable programs that are used to process the signalsreceived by the peripheral interface circuits. The memory 50 stores anoperating system 52 and a plate positioning module 54. Theplate-positioning module 54 is used to control the plate positioncontroller 24. The memory also stores an image capture interface module56, which is used to control the image capture device 30. In addition,the image capture interface module 56 may perform standard imageprocessing tasks.

The components of the system 20 discussed up to this point are known inthe art. U.S. Pat. No. 5,989,835, which is incorporated by reference,describes components of this type. The invention is directed toward theremaining methods, algorithms, computer programs, computer programproducts, and executable programs and instructions in memory 50 as wellas computers and computing machines implementing and executing suchmethods, algorithms, computer programs, and instructions, These programsand instructions perform image-processing tasks in accordance with theinvention.

In one embodiment of the invention, an object identification module 57is stored in memory 50, typically including storage of a set ofexecutable computer program instructions. The object identificationmodule 57 includes executable code to identify objects, such as cellnuclei, from luminescence intensity (“LI”) values secured by imagecapture device 30.

The memory 50 may also store a cell proliferation analysis module 58.The cell proliferation analysis module 58 includes executable code tocount the objects, such as the cell nuclei, identified by the objectidentification module 57. The number of nuclei corresponds to the numberof cells in the captured region of the sample.

The memory 50 may also store a cell cycle analysis module 60. The cellcycle analysis module 60 includes executable code to calculate totalnuclear brightness (“NB”) and standard deviation of nuclear brightness(“SD”) values from LI values corresponding to nuclei secured by imagecapture device 30. Based upon these values, the cell cycle analysismodule 60 then provides information about the cycle phases of thecaptured cells.

The memory 50 may also store a cell death analysis module 62. The celldeath analysis module 62 includes executable code to determine theminimum nuclear luminescence intensity (“MNLI”) value corresponding toone or more nuclei captured by the image capture device 30. Based uponthese MNLI values, the cell death analysis module 62 providesinformation about the viability the captured cells.

The operation of these various modules is described in more detail,below.

4.2 The Object Identification Module

FIG. 2 illustrates one embodiment of processing steps associated withthe operation of object identification module 57. The first processingstep of FIG. 2 is to obtain luminescence intensity values of cellscaptured by image capture device 30 (block 70). A cell sample is placedon sample plate 22. The cells are stained with a luminescent DNA-bindingreporter molecule, such as a fluorescent DNA-binding dye. Virtually anyluminescent DNA-binding dye may be used, including fluorescent minorgroove binding dyes such as indoles, imidazoles, bisbenzimides (e.g.,Hoechst 33258, Hoechst 33342 and Hoechst 34580)4′,6-diamidino-2-phenylindole (DAPI) and fluorescent intercalating dyessuch as phenanthridiniums (e.g., ethidium bromide, propidium iodide(PI), hexidium iodide, dihydroethidium, ethidium homodimers, etc) andacridines (e.g., acridine orange, acridine homodimer,9-amino-6-chloro-2-methoxyacridine (ACMA)). Additional luminescentDNA-binding dyes that may be used are well-known and include, forexample, the myriad dyes available from Molecular Probes, Inc.Preferably, the dye will either not bind RNA or luminesce differentiallywhen bound to RNA (or single-stranded DNA) such that the nuclei ofnucleated cells can be visualized. Of course, skilled artisans willappreciate that if the module is used to identify cells per se, or othercomponents or organelles of cells, other suitable dyes may be used, asare well-known in the art.

Typically, the cells are stained with an amount of reporter moleculethat binds to DNA in a linear range. Useful concentration ranges forproviding linear DNA binding for specific dyes or reporter molecules arethose commonly employed in FACS experiments, and are well-known in theart. For DAPI, it has been found that staining cells with a final DAPIconcentration of about 5 ng/mL yields good results.

Light source 26 illuminates the cell sample. Depending upon the natureof the DNA-binding dye used, the illumination wavelength is selected soas to cause the dye to luminesce. For example, when the cells arestained with a fluorescent dye, an illumination wavelength is selectedthat causes the dye to fluoresce. Excitation wavelengths suitable forparticular dyes are well-known in the art. The image capture device 30subsequently obtains luminescent intensity values produced by theilluminated cells. For nucleated cells, the luminescent intensity valueswill correspond to the nuclei of the cells. Typically, the luminescenceintensity values are associated with individual pixels. If a pluralityof nuclei are captured by image capture device 30, luminescenceintensity values corresponding to individual nuclei can be obtained andcorrelated with their respective nuclei.

The cell nuclei are identified from the luminescence intensity (“LI”)values (also referred to herein as pixel gray values) as outlined inFIG. 2 and illustrated in FIG. 3. Referring to FIG. 3, image A shows adigital image corresponding to a DAPI-stained cellular sample capturedby the image capture device. This image A may be either an image of theraw LI values captured by the image capture device or, alternatively,the image A may be an image that has been processed, for example toremove background luminescence using standard techniques. In this imageA (or digital data corresponding thereto), pixels having a gray valuethat exceeds a first threshold (background) value are identified, andmay be optionally designated as “on.” Pixels having a gray value belowthis first threshold value may be turned “off.” Groupings or clusters of50 or more pixels that have gray values above the first threshold level,and which optionally have a specified roundness parameter (described inmore detail, below), are identified as preliminary objects (defined inblock 72 of FIG. 2 and illustrated in image B of FIG. 3).

The first threshold value will depend upon such parameters as backgroundluminescence, the sensitivity of the dye used, etc., and will beapparent to those of skill in the art. By way of example, the thresholdvalue may be set at a specific interval above measured backgroundluminescence, either by the user or by the object identification module.If set by the module, the threshold value may be determined usingstandard routines for distinguishing signals from background noise. As aspecific example, the threshold value may be determined using the signalto noise (S/N) routine employed by the ImagePro® software packagesupplied with an ArrayScan II® (Cellomics, Inc.) instrument.Alternatively, the first threshold level may be selected by the userfrom a set of predetermined values corresponding to particular reportermolecules.

A first mask (“mask A”) is made from the preliminary objects (clustersof “on” pixels), as represented in block 74 of FIG. 2 and illustrated inimage C of FIG. 3. In this image C, all pixels that correspond to apreliminary object are turned “on” and all pixels that do not correspondto a preliminary object are turned “off.” The mask is dilated usingstandard dilation algorithms. As a specific example, the mask may bedilated for two passes using a 3×3 cross filter, as represented in block76 of FIG. 2 and illustrated in image D of FIG. 3. The dilated mask A issubtracted from the original image (or digital data correspondingthereto) as represented in block 78 of FIG. 2 to yield a subtractedimage as illustrated in image E of FIG. 3. Groupings or clusters of 20or more pixels having gray values that exceed a second threshold valueand that have a specified roundness parameter are identified in thissubtracted image. This is the function described in block 80 of FIG. 2and illustrated in image F of FIG. 3.

The second threshold value may be the same as the first threshold value,or it may be different. If different, it may be determined in the samemanner as the first threshold value based upon the subtracted image (ordigital data corresponding thereto).

The value of the roundness parameter applied (as well as the previouslydescribed optional roundness parameter) will depend upon the overallmorphology of the cells (e.g., circular, oval, rodlike, etc.), and willbe apparent to those of skill in the art. For circular and oval cells,such as most tumor cell lines except for HeLa cells, which are shapedlike a horseshoe, a roundness parameter in the range of 0-2 yields goodresults. For HeLa cells, a roundness parameter of greater than 2 may beapplied. Roundness parameters suitable for cells having other overallmorphologies will be apparent to those of skill in the art. In someembodiments roundness can be calculated using the Cell P2A methoddisclosed in U.S. Patent Application Publication No. US20010041437A1 inwhich the cell perimeter (P) squared is divided by (4π times the cellarea). This is a measure of the deviation of the object from roundness.P2A is a scale-independent measure of cell shape and is more sensitiveto local irregularities in the perimeter. In some embodiments roundnesscan be calculated using the Cell Height Width Ratio Method (“HWR”) whichis the ratio of the length of the cell to the width of the cell andfairly round objects have a HWR value close to 1.0 (US20010041437A1).Other methods of calculating roundness that yield values in the range of0-1 are disclosed in ArrayScan® II System: General Screening ApplicationGuide 7 (Cellomics, Inc. ©1991-2001), incorporated by reference.

In image F, the newly identified objects are defined with boundarylines. A second mask (mask “B”) is made of such newly defined objects,as represented in block 82 of FIG. 2 and illustrated in image G of FIG.3. To make mask B, pixels within the newly defined objects are turned“on” and all others are turned “off,” as illustrated in image G.Undilated mask A and mask B are then added to create a third, summedmask, as represented in block 84 of FIG. 2 and illustrated in image H ofFIG. 3. Clusters of “on” pixels in the summed mask are identified asobjects and counted as nuclei, as represented in block 86 of FIG. 2 andillustrated in image I of FIG. 3. A watershed split routine is performedon the objects identified in image I to obtain outlines of the objects,as represented in block 88 of FIG. 2. The outlines are then applied tothe original image (image A of FIG. 3), as represented in block 90 ofFIG. 2 and illustrated in image J of FIG. 3.

The object identification module 57 illustrated in FIG. 2 may bemodified to incorporate a routine (prior to block 70) to removeluminescence caused by crystals or other precipitated material in thesample. According to this embodiment, the cells are stained with twodifferent dyes that luminesce at two different, distinguishable colors:a first dye that is a DNA-binding dye, as previously described, and asecond dye that does not bind DNA. Dyes suitable for use as the seconddye will be apparent to those of skill in the art. As a specificexample, the cells may be stained with DAPI and fluorescein isocyanate(FITC).

In this alternative embodiment, the image capture device captures twoimages. One including luminescence intensity values of the first,DNA-binding dye (e.g., DAPI) and another including luminescenceintensity values from the second dye (e.g., FITC). Following optionalprocessing to reduce background luminescence, the second image is thensubtracted from the first image. The subtraction removes luminescencecaused by crystals or other particulate matter common to both images.The resultant subtracted image is then used as the original image fromwhich LI values are obtained in block 70 of FIG. 2 (and also correspondsto image A of FIG. 3).

The superior ability of the object identification module 57 to identifyand define objects as compared with standard object identificationmodules is illustrated in FIG. 4A. In FIG. 4A, Panel A provides imagesof DAPI-stained A549 cells that have been treated for 48 hr withdimethylsulfoxide (“DMSO”; 0.2% v/v, vehicle control cells). Panel Bprovides images of DAPI-stained A549 cells that have been treated for 48hr with taxol (30 nM). For each Panel, the center image is the imagedefined by block 70 of FIG. 2. The data were acquired on an ArrayScan IIinstrument (Cellomics, Inc.). The left-hand images include boundarylines defining objects as identified using the default parameters of theImagePro® software supplied with the ArrayScan II instrument. Theright-hand images include boundary lines defining objects as identifiedusing the embodiment of the object identification module outlined inFIG. 2. For both DMSO and taxol-treated cells, differences between theidentification routines, as evidenced by comparing the appropriatecorresponding boxed regions in the right- and left-hand images, areclearly visible. When compared to the nuclei that are identified by askilled worker by visual inspection, which is considered the “goldstandard” for identifying nuclei in images such as those presented inFIGS. 3 & 4, the object identification module of the invention is moreaccurate than conventional object identification routines. Thisincreased accuracy is illustrated in FIG. 4B.

FIG. 4B provides a bar graph illustrating the percentage differencebetween the number of nuclei identified by a handcount and the numberidentified by three different object identification routines: theroutine illustrated in FIG. 2; the default routine used by the ImagePro®software supplied with an ArrayScan II instrument (Cellomics, Inc.); andthe ImagePro® default modified to include a watershed split routine. Inthe bar graph of FIG. 4B, positive percentages indicate overcounting andnegative percentages indicate undercounting. The optimal value, whichcorresponds to that obtained by a hand count, is zero. For all cellpopulations tested (A549 cells treated with DMSO, etoposide, taxol andtwo test compounds—cmpd 1 and cmpd 2), the ImagePro® default routinegreatly under counted the nuclei. On balance, the object identificationroutine of FIG. 2 provided results most comparable to those obtainedwith a hand count, demonstrating the increased accuracy of this routineover the other routines tested.

Other methods of identifying objects may be adapted in accordance withthe principles taught herein to identify objects with accuracies thatapproximate those achieved by visual inspection by a skilled worker, andare also within the scope of the invention. For example, any of a numberof known adaptive thresholding procedures may be used in conjunctionwith a watershed split routine to achieve satisfactory results. Aspecific example of an adaptive thresholding procedure that may beadapted to identify cell nuclei in connection with the principlesthought herein is described in U.S. Pat. No. 5,989,835 (see especiallyCol. 6, line 32 through Col. 7, line 17), which is incorporated hereinby reference.

Once objects have been identified, information corresponding to one ormore identified nuclei in accordance with the other modules describedherein may be obtained based upon the luminescence intensity values ofpixels falling within the outlines of the defined nuclei, as representedby block 88 of FIG. 2.

4.3 The Cell Proliferation Analysis Module

The cell proliferation analysis module 58 provides information about theability of cells to divide and proliferate. In general, the cellproliferation analysis module provides such information by counting thenumber of objects (typically nuclei) identified by the objectidentification module 57. In one embodiment, the cell proliferationanalysis module 57 can be used to screen for and/or identify candidatecompounds having anti-proliferative activity. According to thisembodiment, the proliferation of cells treated with or exposed to acandidate compound of interest can be monitored with the cellproliferation analysis module 58 of the invention. Comparison of theproliferation activity of the treated cells with control cells (e.g.,untreated cells, cells treated with a vehicle or cells treated with aknown anti-proliferative compound) provides information about theability of the candidate compound to inhibit cell proliferation. In aspecific embodiment, samples of equal volume are collected from a cellculture as a function of time and analyzed for proliferation with thecell proliferation analysis module 58 of the invention. Cells that donot show increases in the number of counted nuclei as a function oftime, or that show lower increases in counted nuclei over time thanexpected for the particular cell type being assayed are reported asnon-proliferating cells. Candidate compounds which induce such effectsare reported as having anti-proliferative activity.

In another specific embodiment, adherent cells may be treated withdifferent concentrations of test compound, permitted to incubate for aspecified period time and then analyzed with the cell proliferationanalysis module 58. Plotting the average number of cells in each samplewell as a function of compound concentration provides a curve from whichthe anti-proliferative IC₅₀ (or EC₅₀) can be determined. An example ofsuch an assay carried out with the cell proliferation analysis module 58on taxol-treated A549 cells is provided in FIG. 5. The obtained EC₅₀ of0.0022 μm correlates well with EC₅₀s measured by other methods.

4.4 The Cell Cycle Analysis Module

The cell cycle analysis module 60 provides information about the cyclingor mitotic phase of a cell or population of cells. As a cell divides,its DNA content increases. For cells stained with a DNA-bindingluminescent dye, the increase in DNA content leads to an increase in thetotal luminescence (nuclear brightness) of the identified or definednucleus. The DNA also begins to aggregate. Thus, the DNA goes from beingevenly distributed throughout the entire nucleus to being aggregated atspecific locations within the nucleus. For a cell stained with aluminescent DNA-binding dye, owing to this aggregation, the luminescenceintensity values corresponding to the nuclei change from having auniform distribution with a low standard deviation to being highlydisperse (i.e., very intense/bright values surrounded by very low/darkvalues) with a high standard deviation. The cell cycle analysis module60 calculates total nuclear brightness and standard deviationcoordinates corresponding to nuclei identified by the objectidentification module 57 based upon their respective LI values toprovide information about the cycling or mitotic phases of the cells.Specifically, the coordinates provide information about whether a cellis in the G1, S, G2, M1 or M2 phase or, alternatively the percentages ofcells within a cell population that are in each of these respectivephases.

One embodiment of cell cycle analysis module 60 is represented in FIG.6A. The first processing step of FIG. 6A is to obtain luminescenceintensity values (pixel gray values) corresponding to defined nuclei(block 100), as described above. The gray values of the individualnuclear pixels are summed to provide the total luminescence intensityvalue (or total nuclear brightness “NB”) corresponding to the definednuclei (block 102), The standard deviation of the luminescenceintensities (“SD”) of all the pixels within the defined nuclei is alsocalculated (block 104). A NB versus SD cartesian coordinate is thendefined for each cell (or a SD versus NB coordinate) (block 106). Thecoordinates can be stored in the database 64 for further manipulation,which may include output to a plotting device or a display device. Inone embodiment, a coordinate is displayed on an XY plot of NB vs. SD orSD vs. NB that includes boundary lines defining regions of the plot thatcorrespond to particular phases of the cell cycle. The regions may bepredefined by the cell cycle analysis module, or they may be determinedby the module based upon analysis of similar XY plots of control cellsusing standard clustering techniques. The regions are correlated tospecific phases of the cell cycle based upon their relative positionswithin the NV vs. SD plot and in accordance with the principles taughtbelow. Alternatively, the boundaries may be drawn by the user based uponvisual inspection of an XY plot of control cell or sample cell NB versusSD coordinates. An example of such an XY plot including boundariesdefining the five different phases of the cell cycle is provided in FIG.7.

Alternatively, cell cycle analysis module 60 may include executablecomputer program code or instructions to filter the coordinate through apredetermined plurality of filters, each of which defines coordinatescorresponding to specific phases of the cell cycle (block 108 in FIG.6A). Such filters can be based upon historical data for cells of asimilar type and age as those being assayed, or may be derived from apopulation of control cells based upon the control cell NB versus SDcoordinates using standard clustering techniques. In an alternateembodiment, the filters could be determined and set by the skilledpractitioner for the particular cell age and type under study, forexample by analysis of histogram plots of samples of control cell oreven the test cell populations. If a plurality of cells is analyzed, thecell cycle analysis module 60 may include executable code to determinethe percentage of cells of the plurality in each phase of the cellcycle. An example of an embodiment of cell cycle analysis module 60 thatcalculates percentages of cells in particular phases of the cell cycleis provided in FIG. 6B.

The ability of the cell cycle analysis module 60 to provide informationabout cell cycling or the mitotic phases of a cell population isillustrated in FIG. 7. FIG. 7 provides a histogram of the coordinates ofa population of cells captured by image capture device 30. Cells in theGI phase, S-phase, G2 phase and two M phases are clearly discerniblefrom the histogram, as indicated by the boundaries. Cells in the resting(G1) phase have a normal (1×) DNA content. In addition, their DNA isuniformly distributed throughout their nuclei. As a consequence, cellsin the GI phase have a very narrow distribution of LI values, andtherefore a low SD. Also, since their chromosomes have not begunmultiplying, G1 cells will have lower NB values than cells in the S, G2and M1 phases. On an XY histogram of NB versus SD coordinates, cells inthe resting G1 phase are clustered in the lower left-hand region of thegraph (see FIG. 7).

As the cells cycle to the synthesis (S) phase, the DNA content of thecells increases, such that S-phase cells have a higher NB than G1-phasecells. As a consequence of their increased DNA content (and hence NB),S-phase cells cluster to the right of G1-phase cells on the histogram.

The DNA content continues to increase uniformly throughout the nucleusand reaches its maximal level as the cells cycle through the G2 phase.Again, since the DNA is fairly uniformly distributed throughout thenucleus, cells in the G2 phase have SD values similar to G1- and S-phasecells. These cells cluster to the right of S-phase cells (see FIG. 7).However, in the initial phases of mitosis (M-phase) the chromosomessegregate and begin dividing. In a stained nucleus, the segregationcreates extremely bright spots within the defined nuclei surrounded by adark background. Thus, cells cycling through the M-phase have high NBvalues and high SD values compared to cells in the G1-, S- andG2-phases. As indicated in FIG. 7, the coordinates of cells in earlyM-phase cluster in the upper right-hand corner of the histogram. Asignificant attribute of the cell cycle analysis module 60 is itsability to distinguish early M-phase cells from late phase M-phasecells. Owing to the fact that late M-phase cells have divided but stillhave segregated chromosomes, these cells have a NB similar to G1-phasecells, but have a much higher SD. Thus, these cells can be distinguishedfrom both G1-phase and early M-phase cells with the cell cycle analysismodule of the invention, as illustrated in FIG. 7.

The inset of FIG. 7 provides a pie-chart diagram of the percentages ofcells in each phase of the cell cycle. The cell population analyzed inFIG. 7 was a population of A549 cells treated with 0.2% (v/v) DMSO for48 hr, which could serve as a standard for comparison with similarhistograms for experimental test cell populations, for example, forcomparison with a histogram calculated from a population of identicalcells treated with a candidate compound.

As evidenced by FIG. 7, the cell cycle analysis module 60 of theinvention can distinguish all five phases or phases of the cell cycle.In contrast, information obtained by FACS cannot distinguish all fivephases. In particular, FACS cannot distinguish G2 from M-phase cells.Thus, not only can the cell cycle analysis module of the inventionprovide information about cell cycling faster and at a lower cost thanFACS analyses, the information provided is also of a higher quality andquantity.

Cell cycle data obtained with cell cycle analysis module 60 forcandidate test compounds correlates well with data obtained by FACS(data not shown), validating the method as being useful in screeningassays. In one embodiment of such a screening assay, the percentages ofcells in the various phases of the cell cycle of a population of cellscontacted with or exposed to a candidate compound of interest can becompared to known phase distributions for untreated or vehicle treatedcontrol cells. Alternatively, a control experiment with a sister cultureof synchronous cells can be run simultaneously with the test sample.

An example of cell cycle information obtained with the cell cycleanalysis module of the invention for sister cultures of synchronous A549cells treated with varying concentrations of DMSO, two differentcompounds known to arrest cells in G2 phase (taxol and etoposide) andtwo test compounds being assessed for activity, cmpd 1 and cmpd 2, areprovided in FIG. 8. For FIG. 8, cells were synchronized with doublethymidine treatment. Prior to the last treatment, test compounds wereadded to the cultures and remained therefor the rest of the experiment.The thymidine was then removed, releasing the cells into the cellcycles. Samples were collected at a designated time point, fixed withaldehyde, stained with DAPI (5 ng/mL) and imaged on an ArrayScan IIinstrument (Cellomics, Inc.). The digital image data was analyzed usingthe cell cycle analysis module of the invention. The percentages of cellin the various phases of the cell cycle are indicated in pie-chartformat. The concentrations of test compound added are indicated acrossthe bottom of the FIG. 8. All DMSO-treated samples (vehicle controlsamples) were treated with 0.2% (v/v) DMSO. The various phases of thecell cycle are illustrated on the right-hand most DMSO-treated graph.The numbers above each graph represent the total number of cellsanalyzed in the particular sample. As clearly visible in FIG. 8, DMSOhas no effect on cell cycling. In contrast, both taxol and etoposidearrest the cells in the G2 phase at concentrations as low as 3 μM.

4.5 The Cell Death Analysis Module

FIG. 9A illustrates one embodiment of processing steps associated withthe operation of the cell death analysis module 62. The first processingstep of FIG. 9A is to obtain luminescence intensity (LI) valuescorresponding to defined nuclei of cells captured by the image capturedevice (block 130), as described above. Based upon these LI values, theminimum nuclear luminescence intensity values (“MNLI”) are obtained(block 132). The MNLI value for a nucleus is the lowest LI valuemeasured for that nucleus, for example, the lowest gray value of thepixels within a specific defined nucleus. At this point, the cell deathanalysis module 62 may compare the MNLI values of particular cells to arange of predefined MNLI values indicative of viable cells (block 134).A value falling outside this range identifies the cell as beingnon-viable or dead, whereas a value falling within this range identifiesthe cell as being viable or alive. Alternatively, the cell deathanalysis module 62 may be carried out with populations of cells, asillustrated in FIG. 9B. In this instance, MNLI values for a plurality ofdefined nuclei are obtained (block 142) based upon their LI values(block 140) and the percentage of cells having MNLI values fallingoutside a specified range of MNLI values is calculated (block 144). Thispercentage is then compared with a predefined percentage rangeindicative of a viable cell population (block 146). Cell populationshaving percentages falling within the predefined range are reported asviable populations, whereas percentages falling outside the predefinedrange are reported as non-viable populations.

Skilled artisans will recognize that the range of MNLI values indicativeof viable cells, as well as the percentages of cells that must fallwithin this range, will depend upon a variety of factors, which includebut are not limited to the type of cell being assayed, the age of thecell being assayed, etc. The range of MNLI values or percentages fallingwithin such ranges that are indicative of viable cells may be determinedby the cell death analysis module 62 based upon in Formation (such ascell type, cell age, etc.) input by the user. Alternatively, it may bedefined by the user or calculated from a population of control cells(untreated, vehicle-treated or treated with compounds known to inducecell death).

In one embodiment, the range of MNLI values indicative of viable cellsmay be calculated from control cell MNLI values using standardstatistical analyses. For example, the MNLI values that bound aspecified percentage or confidence interval, for example, 80%, 90%, 95%or a higher percentage, of the control cell MNLI values may be used asboundaries to defined the range of MNLI values indicative of viablecells. As this range is only exemplary, it will be appreciated thathigher or lower percentages may be utilized. As a specified example, theMNLI values that bound 95% of the MNLI values using a standardstatistical analysis yields good results. The boundary values may beused in an absolute sense to define a specific LI range (in absoluteintensity units). Alternatively, the boundary values may be used in arelative sense to define an interval or spread (e.g., ±X intensityunits) of acceptable LI values. When used in a relative sense, thespread or interval may be applied to the statistical mean of MNLI valuesfor a population of test cells to define the range of acceptable MNLIvalues. Once applied, the percentage of test cells falling within (orwithout) the range can be calculated to assess whether the cellpopulation is viable or non-viable. A population of test cells isreported as non-viable when the percentage of test cells having MNLIvalues falling inside the range is less than the confidence percentageor interval used to define the range. For example, if the range of MNLIvalues indicative of viable cells is defined by the 95% confidenceinterval of MNLI values of a population of control cells, then apopulation of test cells is reported as non-viable if less than 95% ofits MNLI values fall inside the defined range (or alternatively, whengreater than 5% of the test MNLI values fall outside the defined range).Images of individual cells, or of populations of cells, may be inspectedvisually to confirm that the cells are non-viable.

Another embodiment of a cell death analysis module 62 of the inventionis illustrated in FIG. 9C. In this alternative embodiment, an MNLIversus NB coordinate is correlated with each defined cell (block 156)and the percentage of cell coordinates falling outside a range ofcoordinates indicative of viable cells is calculated (block 158).

Alternatively, the coordinates can be displayed on an XY graph of, e.g.,NB versus MNLI, and the viability of the cell population assessed byvisual inspection. The graph may include lines bounding a region ofcoordinates indicative of viable cells. The boundaries may bepredetermined information input by the user or based upon experimentsperformed with control cells of a similar type and age of those beingassayed, or they may be obtained from control cells assayed concurrentlywith the test samples.

The ability of the cell death analysis module 62 to provide informationabout the ability of a test compound to induce cell death in a cellpopulation is illustrated in FIG. 10. FIG. 10 provides an XY plot of theNB versus MNLI coordinates of control cells treated with DMSO (blue) acontrol compound that does not induce cell death. The coordinates ofthese DMSO-treated cells form a tight band of MNLI values. Based on astatistical analysis, 95% of the MNLI values measured from thispopulation fall within a range of 481 to 560 intensity units (i.e.,within a range of ±79 intensity units from the statistical mean MNLIvalue). Visual inspection of images of selected nuclei (shown on theright-hand side of FIG. 10) of this population reveals the cells areviable. The MNLI versus NB coordinates for cells treated with etoposide(magenta), a drug known to arrest mitosis but not induce cell death,also form a tight band. Moreover, 99.5% of the etoposide-treated cellsfall within the same band of 481-560 MNLI values. In stark contrast, thecoordinates of a cell population treated with Taxol (red), a drug knownto induce cell death via apoptosis, do not form a narrow band. For thispopulation, only 83% of the cells are within the 481-560 MNLI valuerange defined by the DMSO control cell population. Visual inspection ofimages of etoposide- and taxol-treated cells confirm the viability andnon-viability, respectively, of these two treated populations. Alsoshown in FIG. 10 are data for two test compounds, cmpd 1 (green) andcmpd 2 (yellow). Both MNLI analysis and visual inspection of images ofcells treated with these compounds reveals that these two test compoundsinduced cell death.

The cell-death analysis module of the invention is as accurate as atrained observer, which is considered the “gold standard” ininterpreting cell images. The accuracy is illustrated in FIG. 11, whichprovides a bar graph comparing the percentage of apoptotic cellsdetermined for the cell populations of FIG. 11 using the lowest grayvalue criteria of the cell-death analysis module of the invention withthat determined by visual inspection (hand classification).

4.6 The Multiparameter Assay

The invention also provides a high information content multiparameterassay useful for analyzing cellular samples for cell proliferation, cellcycle phase, cell death and/or for screening compounds for anti-cancerutility. In the high information content assay, the objectidentification module 57 described above is combined with threeadditional modules: the cell proliferation analysis module 58, the cellcycle analysis module 60 and the cell death analysis module 62. Otherembodiments may utilize the modules separately on in any combination.The object identification module 57 identifies and defines nucleicaptured by image capture device 30, for example as described inconnection with FIGS. 2 and 3, supra and the cell proliferation analysismodule 58 counts the identified nuclei. A comparison of the number ofcaptured cell nuclei before and after treatment with a candidatecompound of interest provides information about whether the compoundinhibits cell proliferation. Alternatively, the number of cells may becounted as a function of time after treatment with the candidatecompound to assess whether the treated cells proliferate over time, andhence whether the candidate compound inhibits proliferation. Forexample, an increase in the number of identified cell nuclei as afunction of time is indicative of cell proliferation. No increase overtime is indicative of inhibition of proliferation. A decrease in thenumber of identified nuclei over time is also indicative of inhibitionof proliferation and also may be indicative of cell death. As describedpreviously, the cell proliferation analysis module 58 may also be usedto measure the IC₅₀ or EC₅₀ of cell proliferation in screeningexperiments with varying concentrations of test compound (see, e.g.,FIG. 5).

The cell cycle analysis module 60 determines the cell cycle phase ofidentified cell nuclei captured by image capture device 30, for exampleas described in connection with FIGS. 6-7, supra. A comparison of thepercentage of cells in each phase of the cell cycle before and aftertreatment with a candidate compound of interest provides informationabout whether the compound induces changes in the cycling of the cell.As illustrated with FIG. 8B, the cell cycle analysis module 62 can beused to identify compounds that arrest mitosis.

The cell death analysis module 62 determines the MNLI value or MNLI vs.NB coordinate for each identified cell nucleus captured by image capturedevice 30, for example as described in connection with FIGS. 9 and 10,supra. A comparison of the percentage of MNLI values or coordinatesfalling within the range of MNLI values or coordinate characteristic ofhealthy, viable cells before and after treatment with a candidatecompound of interest provides information about whether the candidatecompound induces cell death.

An advantage of the high information content oncology assay of theinvention is its ability to provide information with respect to thesemultiple parameters (cell proliferation, cell cycling and cell death)simultaneously. Once nuclei are identified using the objectidentification module 57, LI values corresponding to the identifiednuclei are obtained. Information about the various multiple parametersis then provided based upon the measured LI values. Thus, informationabout numerous parameters important to assessing a candidate compound'susefulness as a potential anticancer agent may be assessed in a singleassay.

The multiparameter high information content assay of the invention isextremely flexible and can be carried out in many different formats. Forexample, information about cell proliferation, cell cycling and celldeath may be obtained for a population of control cells (treated oruntreated) and compared with similar information obtained from testcells treated or exposed to a candidate compound of interest.Alternatively, the information from the test cells may be compared toknown information to assess whether the candidate compound induceschanges in the proliferation, cycling or viability of the cells.

The apparatus and high information content assay of the invention wereused to analyze cell proliferation, cell death and cell cycling of cellstreated with DMSO and compounds known to produce cell cycle arrest(e.g., taxol, etoposide, nocodazole). This information was compared withproliferation and cell cycle information obtained by standard BrDU andFACS assay methods, respectively, on sister cultures of synchronouslycycling cells. For the experiment, A549 cells were synchronized withdouble thymidine treatment: cells were treated with 2 mM thymidine for18 hr, placed back into normal media for 8 hr followed by a secondthymidine treatment for 18 hr. Two hours before the end of this secondtreatment, test compounds were added to the cultures and remained therefor the rest of the experiment. The thymidine was then removed from thecultures, releasing the cells into the cell cycle. Samples werecollected at various time points and prepared for analysis. Cells forBrDU assay were ethanol fixed, stained with antibody, incubated withsubstrate and read immediately on a plate reader (a BrDU kit from RocheMolecular was used according to the packaged instructions). Cells forFACS were prepared according to standard methods. Cells for analysisaccording to the invention were fixed with aldehyde, stained with DAPI(5 ng/mL) and imaged on an ArrayScan II (Cellomics, Inc.) instrument.

Comparison of data histograms obtained by FACS and the high informationcontent assay of the invention at 0 and 9 hr post-release time pointsreveals a good correlation between the two methods. However, unlikeFACS, the high information content assay of the invention is able todistinguish all five phases of the cell cycle (see, e.g., FIG. 7).Comparison of compound EC50 values obtained with the assay of theinvention and those obtained with BrDU also yielded a good correlation.

In sum, these experiments demonstrate that information about cellproliferation, cell death and cell cycling can be obtained with a singlehigh information content assay according to the invention. The highinformation content assay acquired this information up to five timesfaster than comparable assays and at a significant cost savings over theother methods (approx. $50/plate savings). The assay has been used toprovide information about cell proliferation, cell death and cellcycling in the context of screening experiments, permitting largenumbers of candidate compounds to be quickly, reliably and accuratelyscreened to assess the candidate compounds for anti-cancer activity.Quite significantly, with the multiparameter high information contentassay of the invention, information as to whether a candidate compoundis cytotoxic or cytostatic, which cannot be obtained from conventionalsingle-parameter assays, can be obtained in a single assay. The assay isalso able to distinguish cells in all five phases of the cell cycle. Inparticular, the G2 and M phases can be readily distinguishable. Thus,the assay of the invention provides cell cycle information that cannotbe obtained with conventional single parameter, FACS or conventionalmultiparameter assays.

The invention having been described, it will be apparent to ordinarilyskilled artisans that numerous changes and modifications can be madethereto without departing from the spirit or the scope of the appendedclaims. As a specific example, skilled artisans will understand thatwhile the high information content assay has been exemplified in thecontext of four modules, once nuclei are identified, the cellproliferation, cell cycle and cell death modules may be used alone or inone or more different combinations.

All publications, patents, patent applications and other documents citedin this application are hereby incorporated by reference in theirentireties for all purposes to the same extent as if each individualpublication, patent, patent application or other document wereindividually indicated to be incorporated by reference for all purposes.

While various specific embodiments have been illustrated and described,it will be appreciated that various changes can be made withoutdeparting from the spirit and scope of the invention(s).

What is claimed is:
 1. A system for analyzing a sample comprising cells,comprising: an image capture device to gather luminescence intensityvalues of nuclei of cells stained with a fluorescent DNA-bindingreporter molecule; and a computer connected to said image capturedevice, said computer including a peripheral interface circuit toreceive said luminescence intensity values, a central processing unitconnected to said peripheral interface circuit, and a memory connectedto said central processing unit, said memory comprising executableinstructions for: calculating the total nuclear fluorescence of eachcell of a population of cells; and determining the cell phase of a cellin said cell population by its total nuclear fluorescence.
 2. The systemof claim 1, wherein said total nuclear brightness is expressed as a meanbrightness for each cell.
 3. The system of claim 1, further comprising adisplay device connected to said computer.
 4. The system of claim 3,further comprising executable instructions for displaying a histogram ofthe cell phase of said cells on said display device.
 5. The system ofclaim 1, wherein said memory further comprise instructions for:comparing total nuclear brightness to standard deviation of nuclearbrightness of a cell to produce a coordinate, and determining the cellcycle phase of said cell using said coordinate.
 6. The system of claim5, wherein said determining comprises filtering said coordinate.
 7. Thesystem of claim 6, wherein said determining comprises filtering saidcoordinate through a plurality of filters, each of which definescoordinates corresponding to specific phases of the cell cycle.
 8. Thesystem of claim 5, wherein said determining includes plotting saidcoordinate on a graph showing total nuclear brightness verses standarddeviation of nuclear brightness of a population of cells.